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Tuesday, December 18, 2018

Faces of risk

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When you say "risk management" to most PMs, what jumps to mind is the quite orthodox conception of risk as the duality of an uncertain future event and the probability of that event happening.

Around these two ideas -- impact and frequency -- we've discussed in this blog and elsewhere the conventional management approaches. This conception is commonly called the "frequentist" view/definition of risk, depending as it does on the frequency of occurrence of a risk event. This is the conception presented in Chapter 11 of the PMBOK.

The big criticism of the frequentist approach -- particularly in project management -- is that too often there is no quantitative back-up or calibration for the probabilities -- an sometimes not for the impact either. This means the PM is just guessing. Sponsors push back and the risk register credibility is put asunder. If you're going to guess at probabilities, skip down to Bayes!

However.. (there's always a however it seems), there are three other conceptions of risk that are not frequentist in their foundation. Here are a few thoughts on each:

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Failure Mode Event Analysis (FMEA): Common in many large scale and complex system projects and used widely in NASA and the US DoD. FMEA focuses on how things fail, and seeks to thwart such failures, thus designing risk out of the environment. Failures are selected for their impact with essentially no regard for frequency. This is because most of the important failures occur so infrequently that statistics are meaningless. Example: run-flat tires. Another example: WMD countermeasures.

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Bayes/Bayes theorem/Bayesians: Bayesians define risk as the gap between a present (or more properly 'a priori') estimate of an event and an observed outcome/value of the actual event (called more properly the posterior value).

There is no hint of frequentist in Bayes; it's simply about gaps -- what we think we know and what it turns out that we should have known. The big criticism -- by frequentists -- is about the 'a priori' estimate: it's often a guess, a 50/50 estimate get things rolling.

Bayes analysis can be quite powerful... it was first conceived in the 17th century by an English mathematician/preacher named Thomas Bayes. However, in WWII it came into its own; it became the basis for much of the theory behind antisubmarine warfare.

But, it can be a flop also: our 'a priori' may be so far off base that there is never a reasonable convergence of the gap no matter how long we observe, or how many observations we take.

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Insufficient controllability, aka anonymous operations: the degree to which we have command of events. Software, particularly, and all anonymous systems generally are considered a "risk" because we lack absolute control. See also: control freak managers. See also the move: 2001: A Space Odyssey. Again, no conception of frequency.